Engineering Investment Process: Making Value Creation Repeatable explores the quantitative steps of a financial investment process.
The authors study how these steps are articulated in order to make any value creation, whatever the asset class, consistent and robust.
The discussion includes factors, portfolio allocation, statistical and economic backtesting, but also the influence of negative rates, dynamical trading, state-space models, stylized facts, liquidity issues, or data biases.
Besides the quantitative concepts detailed here, the reader will find useful references to other works to develop an in-depth understanding of an investment process.
1. Introduction - p. xv 2. List of Acronyms - p. xxxv 3. 1: Understanding the Investment Universe - p. 1 4. 2: Dealing with Risk Factors - p. 61 5. Abstract - p. 61 6. 2.1 Dependence among markets - p. 63 7. 2.2 Linear factor models - p. 94 8. 2.3 Risk factor dynamics: the state-space modeling framework - p. 110 9. 2.4 The liquidity risk factor - p. 134 10. 2.5 Implications of low rates on risk modeling in fixed-income markets - p. 151 11. 3: Active Portfolio Construction - p. 159 12. Abstract - p. 159 13. 3.1 Introduction - p. 159 14. 3.2 A theoretical toolbox for allocation - p. 166 15. 3.3 A focus on mean-variance - p. 172 16. 3.4 Spectral insights for allocation - p. 185 17. 3.5 Allocating using views - p. 203 18. 3.6 Allocating without views - p. 221 19. 3.7 Dynamic trading - p. 234 20. 4: Backtesting and Statistical Significance of Performance - p. 259 21. 5: Gauging Economic Influences on Quantitative Strategies - p. 297 22. Appendix - p. 329 23. Conclusion - p. 347 24. Bibliography - p. 349 25. Index - p. 387
Engineering Investment Process: Making Value Creation Repeatable explores the quantitative steps of a financial investment process.
The authors study how these steps are articulated in order to make any value creation, whatever the asset class, consistent and robust.
The discussion includes factors, portfolio allocation, statistical and economic backtesting, but also the influence of negative rates, dynamical trading, state-space models, stylized facts, liquidity issues, or data biases.
Besides the quantitative concepts detailed here, the reader will find useful references to other works to develop an in-depth understanding of an investment process.
1. Introduction - p. xv 2. List of Acronyms - p. xxxv 3. 1: Understanding the Investment Universe - p. 1 4. 2: Dealing with Risk Factors - p. 61 5. Abstract - p. 61 6. 2.1 Dependence among markets - p. 63 7. 2.2 Linear factor models - p. 94 8. 2.3 Risk factor dynamics: the state-space modeling framework - p. 110 9. 2.4 The liquidity risk factor - p. 134 10. 2.5 Implications of low rates on risk modeling in fixed-income markets - p. 151 11. 3: Active Portfolio Construction - p. 159 12. Abstract - p. 159 13. 3.1 Introduction - p. 159 14. 3.2 A theoretical toolbox for allocation - p. 166 15. 3.3 A focus on mean-variance - p. 172 16. 3.4 Spectral insights for allocation - p. 185 17. 3.5 Allocating using views - p. 203 18. 3.6 Allocating without views - p. 221 19. 3.7 Dynamic trading - p. 234 20. 4: Backtesting and Statistical Significance of Performance - p. 259 21. 5: Gauging Economic Influences on Quantitative Strategies - p. 297 22. Appendix - p. 329 23. Conclusion - p. 347 24. Bibliography - p. 349 25. Index - p. 387
